Stimulation electrode selection

ABSTRACT

Bioelectrical signals may be sensed within a brain of a patient with a plurality of sense electrode combinations. A stimulation electrode combination for delivering stimulation to the patient to manage a patient condition may be selected based on the frequency band characteristics of the sensed signals. In some examples, a stimulation electrode combination associated with the sense electrode combination that sensed a bioelectrical brain signal having a relatively highest relative beta band power level may be selected to deliver stimulation therapy to the patient. Other frequency bands characteristics may also be used to select the stimulation electrode combination.

This application is a continuation of U.S. patent application Ser. No.13/827,537, which was filed on Mar. 14, 2013 and is entitled,“STIMULATION ELECTRODE SELECTION.” U.S. patent application Ser. No.13/827,537 issued as U.S. Pat. No. 8,670,830 on Mar. 12, 2014. U.S.patent application Ser. No. 13/827,537 is a divisional of U.S. patentapplication Ser. No. 12/563,845, which was filed on Sep. 21, 2009, andis entitled, “STIMULATION ELECTRODE SELECTION,” and issued as U.S. Pat.No. 8,428,733 on Apr. 23, 2013. U.S. patent application Ser. No.12/563,845 claims the benefit of U.S. Provisional Patent Application No.61/105,943, which was filed on Oct. 16, 2008 and is entitled,“STIMULATION ELECTRODE SELECTION.” The entire content of U.S. patentapplication Ser. Nos. 13/827,537, 12/563,845, and 61/105,943 isincorporated herein by reference.

TECHNICAL FIELD

The disclosure relates to medical devices, and, more particularly, toconfiguration of therapy parameters for a medical device.

BACKGROUND

Patients afflicted with movement disorders or other neurodegenerativeimpairment, whether by disease or trauma, may experience muscle controland movement problems, such as rigidity, bradykinesia (i.e., slowphysical movement), rhythmic hyperkinesia (e.g., tremor), nonrhythmichyperkinesia (e.g., tics) or akinesia (i.e., a loss of physicalmovement). Movement disorders may be found in patients with Parkinson'sdisease, multiple sclerosis, and cerebral palsy, among other conditions.Delivery of electrical stimulation and/or a fluid (e.g., apharmaceutical drug) by a medical device to one or more sites in apatient, such as a brain, spinal cord, leg muscle or arm muscle, in apatient may help alleviate, and in some cases, eliminate symptomsassociated with movement disorders.

During a programming session, which may occur during implant of themedical device, during a trial session, or during a follow-up sessionafter the medical device is implanted in the patient, a clinician maygenerate one or more therapy programs that provide efficacious therapyto the patient, where each therapy program may define values for a setof therapy parameters. A medical device may deliver therapy to a patientaccording to one or more stored therapy programs. In the case ofelectrical stimulation, the therapy parameters may definecharacteristics of the electrical stimulation waveform to be delivered.Where electrical stimulation is delivered in the form of electricalpulses, for example, the parameters may include an electrodecombination, an amplitude, which may be a current or voltage amplitude,a pulse width, and a pulse rate for the pulses.

SUMMARY

In general, the disclosure is directed toward selecting one or moreelectrodes from an array of electrodes to deliver electrical stimulationto a brain of a patient to provide therapy to manage a patientcondition, such as a movement disorder. The one or more selectedelectrodes used to deliver stimulation may be referred to as astimulation electrode combination, and may include one electrode (e.g.,unipolar stimulation between the electrode and the can) or two or moreelectrodes (e.g., bipolar stimulation). In examples described herein,the stimulation electrode combination may be selected based onbioelectrical signals sensed within the patient's brain. In particular,bioelectrical signals may be sensed within the brain with a plurality ofsense electrode combinations, and the stimulation electrode combinationmay be selected based on frequency domain characteristics of the sensedsignals. For example, the stimulation electrode combination may beselected based on the sense electrode combination that is associatedwith the sensed bioelectrical signal having the greatest beta band power(or energy) to signal power ratio. Other frequency domaincharacteristics and the power levels in other frequency bands may alsobe used to select the stimulation electrode combination. In addition, insome examples, a stimulation electrode combination may be selected basedon an impedance of an electrical path including the stimulationelectrodes.

In one aspect, the disclosure is directed to a method comprising sensinga first bioelectrical signal in a brain of a patient with a first senseelectrode combination, sensing a second bioelectrical signal in thebrain with a second sense electrode combination that is different thanthe first sense electrode combination, determining a frequency domaincharacteristic of each of the first and second bioelectrical signals,selecting at least one of the first or second sense electrodecombinations based on the frequency domain characteristics of the firstand second bioelectrical signals, and selecting a stimulation electrodecombination for delivering electrical stimulation to the brain of thepatient based on the selected at least one of the first or second senseelectrode combinations

In another aspect, the disclosure is directed to a system comprising aplurality of electrodes, a sensing module that senses a firstbioelectrical signal in a brain of a patient with a first senseelectrode combination comprising a first subset of electrodes of theplurality of electrodes and senses a second bioelectrical signal in thebrain with a second sense electrode combination that comprises a secondsubset of electrodes of the plurality of electrodes different than thefirst subset of electrodes, and a processor. The processor determines afrequency domain characteristic of each of the first and secondbioelectrical signals, selects at least one of the first or second senseelectrode combinations based on the frequency domain characteristics ofthe first and second bioelectrical signals, and selects a stimulationelectrode combination for delivering electrical stimulation to the brainof the patient based on the selected at least one of the first or secondsense electrode combinations.

In another aspect, the disclosure is directed to a system comprisingmeans for sensing a first bioelectrical signal in a brain of a patientwith a first sense electrode combination, means for sensing a secondbioelectrical signal in the brain with a second sense electrodecombination that is different than the first sense electrodecombination, means for determining a frequency domain characteristic ofeach of the first and second bioelectrical signals, means for selectingat least one of the first or second sense electrode combinations basedon the frequency domain characteristics of the first and secondbioelectrical signals, and means for selecting a stimulation electrodecombination for delivering electrical stimulation to the brain of thepatient based on the selected at least one of the first or second senseelectrode combinations.

In another aspect, the disclosure is directed to a method comprisingcontrolling a stimulation module to deliver stimulation to a brain of apatient with a first stimulation electrode combination, sensing a firstbioelectrical signal in the brain of the patient with a first senseelectrode combination that is associated with the first stimulationelectrode combination, determining a first frequency domaincharacteristic of the first bioelectrical signal, sensing a secondbioelectrical signal in the brain of the patient with a second senseelectrode combination that is associated with a second stimulationelectrode combination, determining a second frequency domaincharacteristic of the second bioelectrical signal, comparing the firstand second frequency domain characteristics, and controlling thestimulation module to deliver stimulation to the brain of the patientwith the second stimulation electrode combination based on thecomparison.

In another aspect, the disclosure is directed to a system comprising astimulation generator that delivers stimulation to a brain of a patientwith a first stimulation electrode combination, a sensing module thatsenses a first bioelectrical signal in the brain of the patient with afirst sense electrode combination that is associated with the firststimulation electrode combination and senses a second bioelectricalsignal in the brain of the patient with a second sense electrodecombination that is associated with a second stimulation electrodecombination, and a processor. The processor determines a first frequencydomain characteristic of the first bioelectrical signal and a secondfrequency domain characteristic of the second bioelectrical signal,compares the first and second frequency domain characteristics, andcontrols the stimulation module to deliver stimulation to the brain ofthe patient with the second stimulation electrode combination based onthe comparison.

In another aspect, the disclosure is directed to a system comprisingmeans for controlling a stimulation module to deliver stimulation to abrain of a patient with a first stimulation electrode combination, meansfor sensing a first bioelectrical signal in the brain of the patientwith a first sense electrode combination that is associated with thefirst stimulation electrode combination, means for determining a firstfrequency domain characteristic of the first bioelectrical signal, meansfor sensing a second bioelectrical signal in the brain of the patientwith a second sense electrode combination that is associated with asecond stimulation electrode combination, means for determining a secondfrequency domain characteristic of the second bioelectrical signal,means for comparing the first and second frequency domaincharacteristics, and means for controlling the stimulation module todeliver stimulation to the brain of the patient with the secondstimulation electrode combination based on the comparison.

In another aspect, the disclosure is directed to a computer-readablemedium comprising instructions. The instructions cause a programmableprocessor to perform any part of the techniques described herein.

The details of one or more examples of the disclosure are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages of the disclosure will be apparent from thedescription and drawings, and from the claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a conceptual diagram illustrating an example deep brainstimulation (DBS) system.

FIG. 2 is an example spectrogram of a bioelectrical brain signal sensedwithin a brain of a patient.

FIG. 3 is functional block diagram illustrating components of an examplemedical device.

FIG. 4 is a functional block diagram illustrating components of anexample medical device programmer.

FIG. 5 is a flow diagram of an example technique for selecting astimulation electrode combination based on a frequency domaincharacteristic of a bioelectrical signal sensed via a sense electrodecombination.

FIGS. 6A-6D are conceptual power spectral density (PSD) plots ofbioelectrical brain signals sensed via different sense electrodecombinations.

FIG. 7 is a flow diagram of an example technique for determining afrequency band of interest for evaluating sense electrode combinations.

FIG. 8 is a flow diagram of an example technique for evaluatingfrequency domain characteristics of various sense electrodecombinations.

FIG. 9 illustrates an example table that associates various senseelectrode combinations with beta band power levels of bioelectricalsignals sensed within a brain of a patient.

FIG. 10 is a flow diagram of an example technique for evaluating astimulation electrode combination.

DETAILED DESCRIPTION

FIG. 1 is a conceptual diagram illustrating an example therapy system 10that delivers therapy to control a patient condition, such as a movementdisorder or a neurodegenerative impairment of patient 12. Patient 12ordinarily will be a human patient. In some cases, however, therapysystem 10 may be applied to other mammalian or non-mammalian non-humanpatients. While movement disorders and neurodegenerative impairment areprimarily referred to herein, in other examples, therapy system 10 mayprovide therapy to manage symptoms of other patient conditions, such as,but not limited to, seizure disorders or psychological disorders.

A movement disorder or other neurodegenerative impairment may includesymptoms such as, for example, muscle control impairment, motionimpairment or other movement problems, such as rigidity, bradykinesia,rhythmic hyperkinesia, nonrhythmic hyperkinesia, and akinesia. In somecases, the movement disorder may be a symptom of Parkinson's disease.However, the movement disorder may be attributable to other patientconditions. Although movement disorders are primarily referred tothroughout the remainder of the application, the therapy systems andmethods described herein are also useful for controlling symptoms ofother conditions, such as neurodegenerative impairment.

Therapy system 10 includes medical device programmer 14, implantablemedical device (IMD) 16, lead extension 18, and leads 20A and 20B withrespective sets of electrodes 24, 26. In the example shown in FIG. 1,electrodes 24, 26 of leads 20A, 20B are positioned to deliver electricalstimulation to a tissue site within brain 28, such as a deep brain siteunder the dura mater of brain 28 of patient 12. In some examples,delivery of stimulation to one or more regions of brain 28, such as thesubthalamic nucleus, globus pallidus or thalamus, may be an effectivetreatment to manage movement disorders, such as Parkinson's disease.

IMD 16 includes a therapy module that includes a stimulation generatorthat generates and delivers electrical stimulation therapy to patient 12via a subset of electrodes 24, 26 of leads 20A and 20B, respectively.The subset of electrodes 24, 26 that are used to deliver electricalstimulation to patient 12, and, in some cases, the polarity of thesubset of electrodes 24, 26, may be referred to as a stimulationelectrode combination. As described in further detail below, thestimulation electrode combination may be selected based on one or morefrequency domain characteristics of a bioelectrical brain signal that issensed by a sense electrode combination that is associated with thestimulation electrode combination. In some examples, the bioelectricalsignals sensed within brain 28 may reflect changes in electrical currentproduced by the sum of electrical potential differences across braintissue. Examples of bioelectrical brain signals include, but are notlimited to, electrical signals generated from local field potentialswithin one or more regions of brain 28, an electroencephalogram (EEG)signal or an electrocorticogram (ECoG) signal.

In some examples, the bioelectrical brain signals that are used toselect a stimulation electrode combination may be sensed within the sametissue site of brain 28 as the target tissue site for the electricalstimulation. As previously indicated, these tissue sites may includetissue sites within the thalamus, subthalamic nucleus or globus pallidusof brain 28. Thus, in some examples, both a stimulation electrodecombination and a sense electrode combination used to sensebioelectrical brain signals may be selected from the same set ofelectrodes 24, 26.

In some examples, the stimulation electrode combination may be selectedduring a programming session following the implantation of IMD 16 andleads 20A, 20B in patient 12. For example, during the programmingsession, bioelectrical brain signals may be sensed within brain 28 viaeach of at least two different sense electrode combinations. Each senseelectrode combination may include a different subset of two or moreelectrodes 24, 26. Frequency domain characteristics of each of thesensed bioelectrical brain signals may be compared to each other and asense electrode combination may be selected based on the comparison. Anexample of a frequency domain characteristic may include power level (orenergy level) within a particular frequency band. The power level may bedetermined based on, for example, a spectral analysis of a bioelectricalbrain signal. The spectral analysis may indicate the distribution overfrequency of the power contained in a signal, based on a finite set ofdata.

In some examples, the sense electrode combination that sensed thebioelectrical brain signal having the highest relative beta band power(or energy) may be selected. The relative beta band power may be a ratioof the power in a beta band of the sensed signal to the overall power ofthe sensed signal. The selected sense electrode combination may beassociated with a stimulation electrode combination, which may beprogrammed into IMD 16 in order to deliver stimulation therapy to brain28. In this way, the stimulation electrode combination may be selectedbased on a frequency domain characteristic of a bioelectrical brainsignal.

In some examples, other stimulation parameter values may be selectedbased on the frequency domain characteristics of a bioelectrical brainsignal sensed via a sense electrode combination associated with astimulation electrode combination. For example, a beta band power levelmay be associated with a stimulation amplitude value that may provideefficacious therapy to patient 12.

One or more specific frequency bands may be more revealing of a usefultarget tissue site for providing stimulation therapy to patient 12 thanother frequency bands. Processor 40 (FIG. 3) may perform a spectralanalysis of the bioelectrical brain signal in the revealing frequencybands. The spectral analysis of a biosignal may indicate the power levelof each bioelectrical signal within each given frequency band over arange of frequencies. While the beta frequency band is primarilyreferred to herein, in other examples, processor 40 may select astimulation electrode combination based on the power level within one ormore frequency bands other than the beta band. The beta band may includea frequency range of about 10 Hertz (Hz) to about 35 Hz, such as about10 Hz to about 30 Hz or 13 Hz to about 30 Hz.

Some movement disorder symptoms of patient 12, such as bradykinesia, maybe associated with abnormal synchronization of beta frequency bandactivity within particular structures of brain 28 of patient 12. Forexample, FIG. 2 is an example spectrogram of bioelectrical brain signalssensed within a subthalamic nucleus of a brain of a human subject. They-axis of the spectrogram indicates the frequency band of thebioelectrical brain signal, the x-axis indicates time, and the z-axis,which extends substantially perpendicular to the plane of the image ofFIG. 2, as indicated by the color of the spectrogram, indicates a powerlevel of the bioelectrical brain signal. The spectrogram provides athree-dimensional plot of the energy of the frequency content of abioelectrical brain signal as it changes over time.

In a first time period 34, the human subject is in a pathological stateand is not under the influence of therapy to mitigate effects of amovement disorder. As shown in FIG. 2, in the first time period 34, apower level of the bioelectrical brain signal of the human subject in asubset of the beta band 36 is relatively high, as indicated by therelatively intense color in FIG. 2. The subset of the beta band 36 inthe example shown in FIG. 2 includes a frequency range of about 10 Hz toabout 20 Hz. In a second time period 38, the human subject is under theinfluence of pharmaceutical agents to mitigate effects of the movementdisorder. As shown in FIG. 2, compared to the first time period 34, thebeta band activity decreases during the second time period 38 in whichthe human subject is receiving movement disorder therapy.

The spectrogram shown in FIG. 2 demonstrates that a power level in abeta band of a bioelectrical brain signal may be relatively high inpatients suffering from movement disorder symptoms, and the power levelmay decrease upon the receipt of therapy to manage the movement disordersymptoms. Thus, a high beta band power level may be a marker for amovement disorder.

In some patients, identifying the location within brain 28 thatdemonstrates the highest relative beta band activity may indicate thelocation at which electrical stimulation may relatively effectivelysuppress the abnormal synchronization of beta frequency band activityassociated with the patient's movement disorder. The location withinbrain 28 that demonstrates the highest relative beta band activity mayindicate the location within brain 28 that is a suitable stimulationtarget for electrical stimulation to manage the patient's movementdisorder. As a result of directing stimulation to this stimulationtarget that exhibits a relatively high level of beta band energy, theintensity of stimulation that IMD 16 may deliver in order to provideefficacious stimulation therapy may be lower than the intensity ofstimulation that may be required to provide efficacious stimulationtherapy to other tissue sites that may be further from the stimulationtarget or less functionally related to the stimulation target. Anintensity of stimulation may be related to the current or voltageamplitude of a stimulation signal, a frequency of the stimulationsignal, and, if the signal comprises a pulse, a pulse width or pulseshape of the stimulation signal.

In some examples, the sense electrode combination that senses thehighest relative beta band activity within brain 28 may provide the bestrelative efficacy when stimulation therapy is delivered via the subsetof electrodes of the sense electrode combination. Thus, in someexamples, the stimulation electrode combination may comprise the subsetof electrodes of the sense electrode combination. In some examples,electrical stimulation may be delivered to substantially the samelocation at which a bioelectrical brain signal having a relatively highrelative beta band power was sensed in order to effectively suppress theabnormal synchronization of beta frequency band activity associated withthe patient's movement disorder.

In other examples, the stimulation electrode combination may comprise adifferent subset of electrodes than the sense electrode combination. Forexample, a sense electrode combination may include at least twoelectrodes 24, 26 of leads 20A, 20B, whereas a stimulation electrodecombination may include a single electrode of leads 20A, 20B (e.g., toprovide unipolar stimulation) or more than two electrodes. In a unipolarconfiguration, stimulation may be provided between an electrode of oneof the leads 20A, 20B and a housing of IMD 16 or another reference. Inthe case of stimulation electrode combinations, it may be possible formore than one electrode to share a polarity. Sensing in a unipolarconfiguration may not be useful for identifying useful bioelectricalbrain signals because sensing between an electrode of one of the leads20A, 20B and a housing of IMD 16 or another reference may result in thesensing of cardiac activity of patient 12, which may dominate and maskthe brain activity.

If the stimulation electrode combination and an associated senseelectrode combination include at least one different electrode, thestimulation electrode combination and sense electrode combination may bepositioned within different parts of brain 28. The parts may or may notoverlap.

In some examples, the sense electrode combination that senses thehighest relative beta band activity within brain 28 may be mapped to astimulation electrode combination that may provide relativelyefficacious stimulation therapy. For example, the subset of electrodesof the sense electrode combination and the subset of electrodes of thestimulation electrode combination may be related by a functionalrelationship between different regions of brain 28. For example, a senseelectrode combination that senses a bioelectrical signal having arelatively high beta band power within a first part of the thalamus maybe mapped to a second part of the thalamus that is functionallyconnected to first part. This functional relationship may indicate thatif electrical stimulation is delivered to the second part of thethalamus via a particular stimulation electrode combination, anyirregular oscillations or other irregular brain activity within thefirst part of the thalamus may be effectively suppressed.

Selecting one or more stimulation electrode combinations for therapysystem 10 based on sensed bioelectrical brain signals may be useful forminimizing the amount of time required to select efficacious stimulationelectrode combinations. In the example shown in FIG. 1, therapy system10 comprises eight electrodes 24, 26, whereby any combination of theeight electrodes 24, 26 may be selected to provide stimulation therapyto brain 28. In existing techniques, a clinician may randomly select andtest stimulation electrode combinations in order to find an efficaciousstimulation electrode combination. In some cases, the clinician'sknowledge and experience selecting stimulation electrode combinationsmay help limit the amount of time required to select stimulationelectrode combinations. The clinician may select a stimulation electrodecombination based on a balance of side effects experienced by patient 12and the extent to which the symptoms of the patient's movement disorderare mitigated. In these existing techniques, the clinician may notconsider the specific anatomical make-up of brain 28 of patient 12 toselect electrode combinations to test, nor the particular physiologicalcharacteristics of patient 12 or the particular dysfunctional state ofthe patient's brain 28. The existing techniques for selecting andtesting stimulation electrode combinations and identifying a relativelyefficacious stimulation electrode combination may be relatively timeconsuming and tedious.

In contrast, the systems, devices, and techniques described herein forselecting a stimulation electrode combination utilize information thatis specific to patient 12. In particular, sensed bioelectrical brainsignals may provide a clinician with useful information that indicatesan efficacious stimulation electrode combination for patient 12. Theinformation for selecting an efficacious stimulation electrodecombination may be in the form of one or more frequency domaincharacteristics of a bioelectrical brain signal sensed by a particularsense electrode combination. The sensed bioelectrical brain signals arespecific to patient 12 because they are sensed within the patient'sbrain 28, and, therefore, may be used to relatively quickly ascertainthe stimulation electrode combinations that may provide efficacioustherapy to the specific patient 12.

In addition to decreasing the time required to select an efficaciousstimulation electrode combination, the techniques described herein mayalso help decrease amount of expertise or experience required to find anefficacious stimulation electrode combination in an efficient manner.For example, as described in further detail below with reference to FIG.9, programmer 14 or another computing device may automatically evaluateone or more sense electrode combinations and determine which senseelectrode combination is associated with a stimulation electrodecombination that may provide efficacious therapy to patient 12 based onthe bioelectrical brain signals specific to patient 12 and specific tothe actual lead placement within the patient's brain 28.

After selecting electrode combinations in accordance with the systemsand techniques described herein, a clinician, alone or with the aid of acomputing device, such as programmer 14, may select the otherstimulation parameter values that provide efficacious therapy to patient12. These other stimulation parameter values may include, for example, afrequency and amplitude of stimulation signals, and, in the case ofstimulation pulses, a duty cycle and pulse width of the stimulationsignals.

In some examples, after IMD 16 is implanted within patient 12 andprogrammed for chronic therapy delivery, IMD 16 may periodicallyreassess the selected stimulation electrode combination to determinewhether another stimulation electrode combination may provide moreefficacious therapy. For example, a processor of IMD 16 may periodicallysense bioelectrical brain signals with two or more sense electrodecombinations comprising electrodes 24, 26 of leads 20A, 20B,respectively. The processor may determine whether stimulation should bedelivered to brain 28 with a different stimulation electrode combinationbased on an analysis of the frequency band characteristics of the sensedbioelectrical brain signals. For example, the processor of IMD 16 mayswitch the subset of electrodes with which IMD 16 delivers stimulationto patient 12 if the currently selected stimulation electrodecombination is not associated with a sense electrode combination thatsenses the bioelectrical brain signal having the relatively highrelative beta band power. In this way, the stimulation electrodecombination used by IMD 16 to deliver electrical stimulation to patient12 may be dynamically changed in a closed-loop system.

Electrical stimulation generated by IMD 16 may be configured to manage avariety of disorders and conditions. In some examples, the stimulationgenerator of IMD 16 is configured to generate and deliver electricalpulses to patient 12 via electrodes of a selected stimulation electrodecombination. However, in other examples, the stimulation generator ofIMD 16 may be configured to generate and deliver a continuous wavesignal, e.g., a sine wave or triangle wave. In either case, a signalgenerator within IMD 16 may generate the electrical stimulation therapyfor DBS according to a therapy program that is selected at that giventime in therapy. In examples in which IMD 16 delivers electricalstimulation in the form of stimulation pulses, a therapy program mayinclude a set of therapy parameter values, such as a stimulationelectrode combination for delivering stimulation to patient 12, pulsefrequency, pulse width, and a current or voltage amplitude of thepulses. As previously indicated, the stimulation electrode combinationmay indicate the specific electrodes 24, 26 that are selected to deliverstimulation signals to tissue of patient 12 and the respective polarityof the selected electrodes.

IMD 16 may be implanted within a subcutaneous pocket above the clavicle,or, alternatively, the abdomen, back or buttocks of patient 12, on orwithin cranium 32 or at any other suitable site within patient 12.Generally, IMD 16 is constructed of a biocompatible material thatresists corrosion and degradation from bodily fluids. IMD 16 maycomprise a hermetic housing to substantially enclose components, such asa processor, therapy module, and memory.

Implanted lead extension 18 is coupled to IMD 16 via connector 30. Inthe example of FIG. 1, lead extension 18 traverses from the implant siteof IMD 16 and along the neck of patient 12 to cranium 32 of patient 12to access brain 28. In the example shown in FIG. 1, leads 20A and 20B(collectively “leads 20”) are implanted within the right and lefthemispheres, respectively, of patient 12 in order deliver electricalstimulation to one or more regions of brain 28, which may be selectedbased on the patient condition or disorder controlled by therapy system10. Other lead 20 and IMD 16 implant sites are contemplated. Forexample, IMD 16 may be implanted on or within cranium 32, in someexamples. Or leads 20 may be implanted within the same hemisphere or IMD16 may be coupled to a single lead.

Although leads 20 are shown in FIG. 1 as being coupled to a common leadextension 18, in other examples, leads 20 may be coupled to IMD 16 viaseparate lead extensions or directly to connector 30. Leads 20 may bepositioned to deliver electrical stimulation to one or more targettissue sites within brain 28 to manage patient symptoms associated witha movement disorder of patient 12. Leads 20 may be implanted to positionelectrodes 24, 26 at desired locations of brain 28 through respectiveholes in cranium 32. Leads 20 may be placed at any location within brain28 such that electrodes 24, 26 are capable of providing electricalstimulation to target tissue sites within brain 28 during treatment. Forexample, electrodes 24, 26 may be surgically implanted under the duramater of brain 28 or within the cerebral cortex of brain 28 via a burrhole in cranium 32 of patient 12, and electrically coupled to IMD 16 viaone or more leads 20.

Example techniques for delivering therapy to manage a movement disorderare described in U.S. Pat. No. 8,121,694 to Molnar et al., entitled,“THERAPY CONTROL BASED ON A PATIENT MOVEMENT STATE,” which issued onFeb. 21, 2012, and is incorporated herein by reference in its entirety.In some examples described by U.S. Pat. No. 8,121,694 to Molnar et al.,a brain signal, such as an EEG or ECoG signal, may be used to determinewhether a patient is in a movement state or a rest state. The movementstate includes the state in which the patient is generating thoughts ofmovement (i.e., is intending to move), attempting to initiate movementor is actually undergoing movement. The movement state or rest statedetermination may then be used to control therapy delivery. For example,upon detecting a movement state of the patient, therapy delivery may beactivated in order to help patient 12 initiate movement or maintainmovement, and upon detecting a rest state of patient 12, therapydelivery may be deactivated or otherwise modified.

In the example shown in FIG. 1, electrodes 24, 26 of leads 20 are shownas ring electrodes. Ring electrodes may be used in DBS applicationsbecause they are relatively simple to program and are capable ofdelivering an electrical field to any tissue adjacent to electrodes 24,26. In other examples, electrodes 24, 26 may have differentconfigurations. For examples, in some examples, at least some of theelectrodes 24, 26 of leads 20 may have a complex electrode arraygeometry that is capable of producing shaped electrical fields. Thecomplex electrode array geometry may include multiple electrodes (e.g.,partial ring or segmented electrodes) around the outer perimeter of eachlead 20, rather than one ring electrode. In this manner, electricalstimulation may be directed to a specific direction from leads 20 toenhance therapy efficacy and reduce possible adverse side effects fromstimulating a large volume of tissue. In some examples, a housing of IMD16 may include one or more stimulation and/or sensing electrodes. Inalternative examples, leads 20 may have shapes other than elongatedcylinders as shown in FIG. 1. For example, leads 20 may be paddle leads,spherical leads, bendable leads, or any other type of shape effective intreating patient 12.

In the example shown in FIG. 3, IMD 16 includes a memory 42 to store aplurality of therapy programs 54 that each defines a set of therapyparameter values. In some examples, IMD 16 may select a therapy programfrom memory 42 based on various parameters, such as a detected patientactivity level, a detected patient state, based on the time of day, andthe like. IMD 16 may generate electrical stimulation based on theselected therapy program to manage the patient symptoms associated witha movement disorder.

During a trial stage in which IMD 16 is evaluated to determine whetherIMD 16 provides efficacious therapy to patient 12, a plurality oftherapy programs may be tested and evaluated for efficacy. In addition,one or more stimulation electrode combinations may be selected for theone or more therapy programs based on frequency band characteristics ofsensed bioelectrical brain signals, as described in further detailbelow. Therapy programs may be selected for storage within IMD 16 basedon the results of the trial stage.

During chronic therapy in which IMD 16 is implanted within patient 12for delivery of therapy on a non-temporary basis, IMD 16 may generateand deliver stimulation signals to patient 12 according to differenttherapy programs 54. In addition, in some examples, patient 12 maymodify the value of one or more therapy parameter values within a singlegiven program or switch between programs in order to alter the efficacyof the therapy as perceived by patient 12 with the aid of programmer 14.Memory 42 of IMD 16 may store instructions defining the extent to whichpatient 12 may adjust therapy parameters, switch between programs, orundertake other therapy adjustments. Patient 12 may generate additionalprograms for use by IMD 16 via external programmer 14 at any time duringtherapy or as designated by the clinician.

External programmer 14 wirelessly communicates with IMD 16 as needed toprovide or retrieve therapy information. Programmer 14 is an externalcomputing device that the user, e.g., the clinician and/or patient 12,may use to communicate with IMD 16. For example, programmer 14 may be aclinician programmer that the clinician uses to communicate with IMD 16and program one or more therapy programs for IMD 16. Alternatively,programmer 14 may be a patient programmer that allows patient 12 toselect programs and/or view and modify therapy parameters. The clinicianprogrammer may include more programming features than the patientprogrammer. In other words, more complex or sensitive tasks may only beallowed by the clinician programmer to prevent an untrained patient frommaking undesired changes to IMD 16.

Programmer 14 may be a hand-held computing device with a displayviewable by the user and an interface for providing input to programmer14 (i.e., a user input mechanism). For example, programmer 14 mayinclude a small display screen (e.g., a liquid crystal display (LCD) ora light emitting diode (LED) display) that presents information to theuser. In addition, programmer 14 may include a touch screen display,keypad, buttons, a peripheral pointing device or another input mechanismthat allows the user to navigate though the user interface of programmer14 and provide input. If programmer 14 includes buttons and a keypad,the buttons may be dedicated to performing a certain function, i.e., apower button, or the buttons and the keypad may be soft keys that changein function depending upon the section of the user interface currentlyviewed by the user. Alternatively, the screen (not shown) of programmer14 may be a touch screen that allows the user to provide input directlyto the user interface shown on the display. The user may use a stylus ortheir finger to provide input to the display.

In other examples, programmer 14 may be a larger workstation or aseparate application within another multi-function device, rather than adedicated computing device. For example, the multi-function device maybe a notebook computer, tablet computer, workstation, cellular phone,personal digital assistant or another computing device that may run anapplication that enables the computing device to operate as medicaldevice programmer 14. A wireless adapter coupled to the computing devicemay enable secure communication between the computing device and IMD 16.

When programmer 14 is configured for use by the clinician, programmer 14may be used to transmit initial programming information to IMD 16. Thisinitial information may include hardware information, such as the typeof leads 20 and the electrode arrangement, the position of leads 20within brain 28, the configuration of electrode array 24, 26, initialprograms defining therapy parameter values, and any other informationthe clinician desires to program into IMD 16. Programmer 14 may also becapable of completing functional tests (e.g., measuring the impedance ofelectrodes 24, 26 of leads 20).

The clinician may also store therapy programs within IMD 16 with the aidof programmer 14. During a programming session, the clinician maydetermine one or more therapy programs that may provide efficacioustherapy to patient 12 to address symptoms associated with one or moredifferent patient states, such as a sleep state, movement state or reststate. For example, the clinician may select one or more stimulationelectrode combinations with which stimulation is delivered to brain 28.During the programming session, patient 12 may provide feedback to theclinician as to the efficacy of the specific program being evaluated orthe clinician may evaluate the efficacy based on one or morephysiological parameters of patient (e.g., muscle activity or muscletone). Programmer 14 may assist the clinician in thecreation/identification of therapy programs by providing a methodicalsystem for identifying potentially beneficial therapy parameter values.

As described in commonly-assigned U.S. Patent Application PublicationNo. 2009/0192556 by Jianping Wu et al., entitled, “SLEEP STAGEDETECTION,” which was filed on Sep. 25, 2008 and published on Jul. 30,2009, and is incorporated herein by reference in its entirety, aparticular sleep stage of a patient's sleep state may be detected basedon a frequency characteristic of a biosignal from a brain of thepatient. The frequency characteristic of the biosignal may include, forexample, a power level (or energy) within one or more frequency bands ofthe biosignal, a ratio of the power level in two or more frequencybands, a correlation in change of power between two or more frequencybands, a pattern in the power level of one or more frequency bands overtime, and the like. Example sleep stages include, for example, Stage 1(also referred to as Stage N1 or S1), Stage 2 (also referred to as StageN2 or S2), Deep Sleep (also referred to as slow wave sleep), and rapideye movement (REM). The Deep Sleep stage may include multiple sleepstages, such as Stage N3 (also referred to as Stage S3) and Stage N4(also referred to as Stage S4). In some cases, patient 12 may cyclethrough the Stage 1, Stage 2, Deep Sleep, REM sleep stages more thanonce during a sleep state. The Stage 1, Stage 2, and Deep Sleep stagesmay be considered non-REM (NREM) sleep stages.

Therapy delivered to patient 12 during the sleep state may be controlledbased on a determined sleep stage. For example, a therapy program may beselected based on the detected sleep stage or a therapy program may bemodified based on the detected sleep stage. Therapy to the patientduring the detected sleep stage may be delivered according to theselected or modified therapy program. The stored therapy programs 54 maybe, for example, associated with different sleep stages.

Programmer 14 may also be configured for use by patient 12. Whenconfigured as a patient programmer, programmer 14 may have limitedfunctionality (compared to a clinician programmer) in order to preventpatient 12 from altering critical functions of IMD 16 or applicationsthat may be detrimental to patient 12. In this manner, programmer 14 mayonly allow patient 12 to adjust values for certain therapy parameters orset an available range of values for a particular therapy parameter.

Programmer 14 may also provide an indication to patient 12 when therapyis being delivered, when patient input has triggered a change in therapyor when the power source within programmer 14 or IMD 16 needs to bereplaced or recharged. For example, programmer 14 may include an alertLED, may flash a message to patient 12 via a programmer display,generate an audible sound or somatosensory cue to confirm patient inputwas received, e.g., to indicate a patient state or to manually modify atherapy parameter.

Whether programmer 14 is configured for clinician or patient use,programmer 14 is configured to communicate to IMD 16 and, optionally,another computing device, via wireless communication. Programmer 14, forexample, may communicate via wireless communication with IMD 16 usingradio frequency (RF) telemetry techniques known in the art. Programmer14 may also communicate with another programmer or computing device viaa wired or wireless connection using any of a variety of local wirelesscommunication techniques, such as RF communication according to the802.11 or Bluetooth specification sets, infrared (IR) communicationaccording to the IRDA specification set, or other standard orproprietary telemetry protocols. Programmer 14 may also communicate withother programming or computing devices via exchange of removable media,such as magnetic or optical disks, memory cards or memory sticks.Further, programmer 14 may communicate with IMD 16 and anotherprogrammer via remote telemetry techniques known in the art,communicating via a local area network (LAN), wide area network (WAN),public switched telephone network (PSTN), or cellular telephone network,for example.

Therapy system 10 may be implemented to provide chronic stimulationtherapy to patient 12 over the course of several months or years.However, system 10 may also be employed on a trial basis to evaluatetherapy before committing to full implantation. If implementedtemporarily, some components of system 10 may not be implanted withinpatient 12. For example, patient 12 may be fitted with an externalmedical device, such as a trial stimulator, rather than IMD 16. Theexternal medical device may be coupled to percutaneous leads or toimplanted leads via a percutaneous extension. If the trial stimulatorindicates DBS system 10 provides effective treatment to patient 12, theclinician may implant a chronic stimulator within patient 12 forrelatively long-term treatment.

FIG. 3 is a functional block diagram illustrating components of anexample IMD 16. In the example shown in FIG. 3, IMD 16 includesprocessor 40, memory 42, stimulation generator 44, sensing module 46,switch module 48, telemetry module 50, and power source 52. Memory 42may include any volatile or non-volatile media, such as a random accessmemory (RAM), read only memory (ROM), non-volatile RAM (NVRAM),electrically erasable programmable ROM (EEPROM), flash memory, and thelike. Memory 42 may store computer-readable instructions that, whenexecuted by processor 40, cause IMD 16 to perform various functions.

As previously discussed, in the example shown in FIG. 3, memory 42stores therapy programs 54, sense electrode combinations and associatedstimulation electrode combinations 56, and operating instructions 58 inseparate memories within memory 42 or separate areas within memory 42.In addition, in some examples, memory 42 may store a bioelectrical brainsignal sensed via at least some of the stored sense electrodecombinations and/or one or more frequency band characteristics of thebioelectrical brain signals. Each stored therapy program 52 defines aparticular program of therapy in terms of respective values forelectrical stimulation parameters, such as a stimulation electrodecombination, electrode polarity, current or voltage amplitude, pulsewidth, and pulse rate. In some examples, the therapy programs may bestored as a therapy group, which defines a set of therapy programs withwhich stimulation may be generated. The stimulation signals defined bythe therapy programs of the therapy group may be delivered together onan overlapping or non-overlapping (e.g., time-interleaved) basis.

Sense and stimulation electrode combinations 56 stores sense electrodecombinations and associated stimulation electrode combinations. Asdescribed above, in some examples, the sense and stimulation electrodecombinations may include the same subset of electrodes 24, 26, or mayinclude different subsets of electrodes. Operating instructions 58 guidegeneral operation of IMD 16 under control of processor 40, and mayinclude instructions for measuring the impedance of electrodes 24, 26and/or determining the distance between electrodes 24, 26.

Stimulation generator 44, under the control of processor 40, generatesstimulation signals for delivery to patient 12 via selected combinationsof electrodes 24, 26. An example range of electrical stimulationparameters believed to be effective in DBS to manage a movement disorderof patient include:

1. Frequency: between approximately 100 Hz and approximately 500 Hz,such as approximately 130 Hz.

2. Voltage Amplitude: between approximately 0.1 volts and approximately50 volts, such as between approximately 0.5 volts and approximately 20volts, or approximately 5 volts.

3. Current Amplitude: A current amplitude may be defined as thebiological load in which the voltage is delivered. In acurrent-controlled system, the current amplitude, assuming a lower levelimpedance of approximately 500 ohms, may be between approximately 0.2milliAmps to approximately 100 milliAmps, such as between approximately1 milliAmps and approximately 40 milliAmps, or approximately 10milliAmps. However, in some examples, the impedance may range betweenabout 200 ohms and about 2 kiloohms.

4. Pulse Width: between approximately 10 microseconds and approximately5000 microseconds, such as between approximately 100 microseconds andapproximately 1000 microseconds, or between approximately 180microseconds and approximately 450 microseconds.

Accordingly, in some examples, stimulation generator 44 generateselectrical stimulation signals in accordance with the electricalstimulation parameters noted above. Other ranges of therapy parametervalues may also be useful, and may depend on the target stimulation sitewithin patient 12, which may or may not be within brain 28. Whilestimulation pulses are described, stimulation signals may be of anyform, such as continuous-time signals (e.g., sine waves) or the like.

In each of the examples described herein, if stimulation generator 44shifts the delivery of stimulation energy between two therapy programs,processor 40 of IMD 16 may provide instructions that cause stimulationgenerator 44 to time-interleave stimulation energy between the electrodecombinations of the two therapy programs, as described incommonly-assigned U.S. Pat. No. 7,519,431 to Steven Goetz et al.,entitled, “SHIFTING BETWEEN ELECTRODE COMBINATIONS IN ELECTRICALSTIMULATION DEVICE,” and issued on Apr. 14, 2009, the entire content ofwhich is incorporated herein by reference. In the time-interleaveshifting example, the amplitudes of the electrode combinations of thefirst and second therapy program are ramped downward and upward,respectively, in incremental steps until the amplitude of the secondelectrode combination reaches a target amplitude. The incremental stepsmay be different between ramping downward or ramping upward. Theincremental steps in amplitude can be of a fixed size or may vary, e.g.,according to an exponential, logarithmic or other algorithmic change.When the second electrode combination reaches its target amplitude, orpossibly before, the first electrode combination can be shut off. Othertechniques for shifting the delivery of stimulation signals between twotherapy programs may be used in other examples.

Processor 40 may include any one or more of a microprocessor, acontroller, a digital signal processor (DSP), an application specificintegrated circuit (ASIC), a field-programmable gate array (FPGA),discrete logic circuitry, and the functions attributed to processor 40herein may be embodied as firmware, hardware, software or anycombination thereof. Processor 40 controls stimulation generator 44according to therapy programs 52 stored in memory 42 to apply particularstimulation parameter values specified by one or more of programs, suchas amplitude, pulse width, and pulse rate.

In the example shown in FIG. 3, the set of electrodes 24 includeselectrodes 24A, 24B, 24C, and 24D, and the set of electrodes 26 includeselectrodes 26A, 26B, 26C, and 26D. Processor 40 also controls switchmodule 48 to apply the stimulation signals generated by stimulationgenerator 44 to selected combinations of electrodes 24, 26. Inparticular, switch module 48 may couple stimulation signals to selectedconductors within leads 20, which, in turn, deliver the stimulationsignals across selected electrodes 24, 26. Switch module 46 may be aswitch array, switch matrix, multiplexer, or any other type of switchingmodule configured to selectively couple stimulation energy to selectedelectrodes 24, 26 and to selectively sense bioelectrical brain signalswith selected electrodes 24, 26. Hence, stimulation generator 44 iscoupled to electrodes 24, 26 via switch module 46 and conductors withinleads 20. In some examples, however, IMD 16 does not include switchmodule 46.

Stimulation generator 44 may be a single channel or multi-channelstimulation generator. In particular, stimulation generator 44 may becapable of delivering, a single stimulation pulse, multiple stimulationpulses or continuous signal at a given time via a single electrodecombination or multiple stimulation pulses at a given time via multipleelectrode combinations. In some examples, however, stimulation generator44 and switch module 48 may be configured to deliver multiple channelson a time-interleaved basis. For example, switch module 48 may serve totime divide the output of stimulation generator 44 across differentelectrode combinations at different times to deliver multiple programsor channels of stimulation energy to patient 12.

As described in further detail with reference to FIG. 9, in someexamples, processor 40 may dynamically change the selected combinationsof electrodes 24, 26, i.e., the stimulation electrode combination, basedon one or more frequency domain characteristics of bioelectrical signalssensed within brain 28. Sensing module 46, under the control ofprocessor 40, may sense bioelectrical brain signals and provide thesensed bioelectrical brain signals to processor 40. Processor 40 maycontrol switch module 48 to couple sensing module 46 to a selectedcombinations of electrodes 24, 26, i.e., a sense electrode combination.In this way, IMD 16 is configured such that sensing module 46 may sensebioelectrical brain signals with a plurality of different senseelectrode combinations. Switch module 48 may be electrically coupled tothe selected electrodes 24, 26 via the conductors within the respectiveleads 20, which, in turn, deliver the bioelectrical brain signal sensedacross the selected electrodes 24, 26 to sensing module 46. Thebioelectrical brain signal may include electrical signals that areindicative of electrical activity within brain 28 of patient 12.

Although sensing module 46 is incorporated into a common housing withstimulation generator 44 and processor 40 in FIG. 3, in other examples,sensing module 46 may be in a separate housing from IMD 16 and maycommunicate with processor 40 via wired or wireless communicationtechniques. Example bioelectrical brain signals include, but are notlimited to, a signal generated from local field potentials within one ormore regions of brain 28. EEG and ECoG signals are examples of localfield potentials that may be measured within brain 28. However, localfield potentials may include a broader genus of electrical signalswithin brain 28 of patient 12.

Processor 40 may analyze the bioelectrical brain signal, e.g., afrequency domain characteristic of the biosignal, to evaluate differentstimulation electrode combinations. As previously indicated, astimulation electrode combination may be associated with a senseelectrode combination in memory 42. Processor 40 may evaluate differentstimulation electrode combinations by, at least in part, sensingbioelectrical brain signals with the sense electrode combinationassociated with a respective one of the stimulation electrodecombinations and analyzing a frequency domain characteristic of thesensed bioelectrical brain signal.

A frequency domain characteristic of the biosignal may include, forexample, a power level (or energy) within one or more frequency bands ofthe biosignal, a ratio of the power level in two or more frequencybands, a correlation in change of power between two or more frequencybands, a pattern in the power level of one or more frequency bands overtime, and the like. In some examples, as described with reference toFIG. 5, processor 40 may adjust a stimulation electrode combination orotherwise select a stimulation electrode combination by selecting astimulation electrode combination that is associated with the senseelectrode combination that sensed the bioelectrical brain signalcomprising the greatest relative beta band power compared to the othersensed bioelectrical brain signals. In other examples, processor 40 mayselect a stimulation electrode combination that is associated with thesense electrode combination that sensed a bioelectrical brain signalcomprising a power level in a particular frequency band above athreshold value, which may be stored in memory 42.

Telemetry module 50 supports wireless communication between IMD 16 andan external programmer 14 or another computing device under the controlof processor 40. Processor 40 of IMD 16 may receive, as updates toprograms, values for various stimulation parameters such as amplitudeand electrode combination, from programmer 14 via telemetry module 50.The updates to the therapy programs may be stored within therapyprograms 54 portion of memory 42. Telemetry module 50 in IMD 16, as wellas telemetry modules in other devices and systems described herein, suchas programmer 14, may accomplish communication by radiofrequency (RF)communication techniques. In addition, telemetry module 50 maycommunicate with external medical device programmer 14 via proximalinductive interaction of IMD 16 with programmer 14. Accordingly,telemetry module 50 may send information to external programmer 14 on acontinuous basis, at periodic intervals, or upon request from IMD 16 orprogrammer 14.

Power source 52 delivers operating power to various components of IMD16. Power source 52 may include a small rechargeable or non-rechargeablebattery and a power generation circuit to produce the operating power.Recharging may be accomplished through proximal inductive interactionbetween an external charger and an inductive charging coil within IMD16. In some examples, power requirements may be small enough to allowIMD 16 to utilize patient motion and implement a kineticenergy-scavenging device to trickle charge a rechargeable battery. Inother examples, traditional batteries may be used for a limited periodof time.

FIG. 4 is a conceptual block diagram of an example external medicaldevice programmer 14, which includes processor 60, memory 62, telemetrymodule 64, user interface 66, and power source 68. Processor 60 controlsuser interface 66 and telemetry module 64, and stores and retrievesinformation and instructions to and from memory 62. Programmer 14 may beconfigured for use as a clinician programmer or a patient programmer.Processor 60 may comprise any combination of one or more processorsincluding one or more microprocessors, DSPs, ASICs, FPGAs, or otherequivalent integrated or discrete logic circuitry. Accordingly,processor 60 may include any suitable structure, whether in hardware,software, firmware, or any combination thereof, to perform the functionsascribed herein to processor 60.

A user, such as a clinician or patient 12, may interact with programmer14 through user interface 66. User interface 66 includes a display (notshown), such as a LCD or LED display or other type of screen, to presentinformation related to the therapy, such as information related tobioelectrical signals sensed via a plurality of sense electrodecombinations. In addition, user interface 66 may include an inputmechanism to receive input from the user. The input mechanisms mayinclude, for example, buttons, a keypad (e.g., an alphanumeric keypad),a peripheral pointing device or another input mechanism that allows theuser to navigate though user interfaces presented by processor 60 ofprogrammer 14 and provide input.

If programmer 14 includes buttons and a keypad, the buttons may bededicated to performing a certain function, i.e., a power button, or thebuttons and the keypad may be soft keys that change in functiondepending upon the section of the user interface currently viewed by theuser. Alternatively, the screen (not shown) of programmer 14 may be atouch screen that allows the user to provide input directly to the userinterface shown on the display. The user may use a stylus or theirfinger to provide input to the display. In other examples, userinterface 66 also includes audio circuitry for providing audibleinstructions or sounds to patient 12 and/or receiving voice commandsfrom patient 12, which may be useful if patient 12 has limited motorfunctions. Patient 12, a clinician or another user may also interactwith programmer 14 to manually select therapy programs, generate newtherapy programs, modify therapy programs through individual or globaladjustments, and transmit the new programs to IMD 16.

In some examples, at least some of the control of therapy delivery byIMD 16 may be implemented by processor 60 of programmer 14. For example,in some examples, processor 60 may receive a bioelectrical brain signalfrom IMD 16 or from a sensing module that is separate from IMD 16. Theseparate sensing module may, but need not be, implanted within patient12. In some examples, processor 60 may evaluate one or more stimulationelectrode combinations based on a frequency component of a bioelectricalbrain signals sensed with the one or more sense electrode combinationsassociated with at least one of the stimulation electrode combinations.Processor 60 may select a stimulation electrode combination for IMD 16based on the analysis of the frequency domain characteristics of thesensed bioelectrical brain signals. In some cases, processor 60 maytransmit a signal to IMD 16 to instruct IMD 16 to switch stimulationelectrode combinations.

Processor 40 of IMD 16 may receive the signal from programmer 14 via itsrespective telemetry module 50 (FIG. 3). Processor 40 of IMD 16 mayswitch stimulation electrode combinations by selecting a stored therapyprogram from memory 42 based on the signal from processor 60 ofprogrammer 14. Alternatively, processor 60 of programmer 14 may select atherapy program or a specific stimulation electrode combination andtransmit a signal to IMD 16, where the signal indicates the therapyparameter values to be implemented by IMD 16 to help improve theefficacy of the stimulation to manage the patient's movement disorder.The indication may be, for example, an alphanumeric identifier or symbolthat is associated with the therapy program in memory 42 of IMD 16.

Memory 62 may include instructions for operating user interface 66 andtelemetry module 64, and for managing power source 68. Memory 62 mayalso store any therapy data retrieved from IMD 16 during the course oftherapy. The clinician may use this therapy data to determine theprogression of the patient condition in order to predict futuretreatment. Memory 62 may include any volatile or nonvolatile memory,such as RAM, ROM, EEPROM or flash memory. Memory 62 may also include aremovable memory portion that may be used to provide memory updates orincreases in memory capacities. A removable memory may also allowsensitive patient data to be removed before programmer 14 is used by adifferent patient.

Wireless telemetry in programmer 14 may be accomplished by RFcommunication or proximal inductive interaction of external programmer14 with IMD 16. This wireless communication is possible through the useof telemetry module 64. Accordingly, telemetry module 64 may be similarto the telemetry module contained within IMD 16. In alternativeexamples, programmer 14 may be capable of infrared communication ordirect communication through a wired connection. In this manner, otherexternal devices may be capable of communicating with programmer 14without needing to establish a secure wireless connection.

Power source 68 delivers operating power to the components of programmer14. Power source 68 may include a battery and a power generation circuitto produce the operating power. In some examples, the battery may berechargeable to allow extended operation. Recharging may be accomplishedby electrically coupling power source 68 to a cradle or plug that isconnected to an alternating current (AC) outlet. In addition, rechargingmay be accomplished through proximal inductive interaction between anexternal charger and an inductive charging coil within programmer 14. Inother examples, traditional batteries (e.g., nickel cadmium or lithiumion batteries) may be used. In addition, programmer 14 may be directlycoupled to an alternating current outlet to operate. Power source 68 mayinclude circuitry to monitor power remaining within a battery. In thismanner, user interface 66 may provide a current battery level indicatoror low battery level indicator when the battery needs to be replaced orrecharged. In some cases, power source 68 may be capable of estimatingthe remaining time of operation using the current battery.

FIG. 5 is a flow diagram illustrating an example technique thatprocessor 40 of IMD 16 may implement in order to select a stimulationelectrode combination for delivering efficacious stimulation therapy tobrain 28 of patient 12. While FIG. 5, as well as FIGS. 7 and 10, areprimarily described with reference to processor 40 of IMD 16, in otherexamples, processor 60 of programmer 14 or a processor of anothercomputing device may perform any one or more parts of the techniquesdescribed herein, such as the techniques described with reference toFIGS. 5, 7, and 10.

Processor 40 of IMD 16 may control sensing module 46 (FIG. 3) to sensebioelectrical brain signals with each of a plurality of sense electrodecombinations (70). For example, switch module 48 (FIG. 3), under thecontrol of processor 40, may selectively couple sensing module 46 to afirst subset of electrodes 24, 26, and sensing module 46 may sense afirst local field potential within brain 28 via the first subset ofelectrodes 24, 26. This first subset of electrodes may also be referredto as a first sense electrode combination. Processor 40 may store thefirst bioelectrical brain signal resulting from the measurement of thefirst local field potential within brain 28 via the first subset ofelectrodes 24, 26 within memory 42 of IMD 16.

Sensing module 48 may subsequently selectively couple sensing module 46to a second subset of electrodes 24, 26, i.e., a second sense electrodecombination, which differs from the first subset by at least oneelectrode. Sensing module 46 may sense a local field potential withinbrain 28 via the second subset of electrodes 24, 26. Processor 40 maystore the second bioelectrical brain signal resulting from themeasurement of the local field potential within brain 28 via the secondsubset of electrodes 24, 26 within memory 42 of IMD 16. Processor 40 maycontinue sensing bioelectrical brain signals within brain 28 with anysuitable number of sense electrode combinations. The sense electrodecombinations may be stored in memory 42 of IMD 16 or a memory of anotherdevice.

Processor 40 may determine a relative beta band power of each sensedbioelectrical brain signal (72). In some examples, sensing module 46 mayinclude circuitry to tune to and extract a power level of a particularfrequency band of a sensed bioelectrical brain signal. Thus, the powerlevel of a particular frequency band of a sensed bioelectrical brainsignal may be extracted prior to digitization of the signal by processor40. By tuning to and extracting the power level of a particularfrequency band before the signal is digitized, it may be possible to runfrequency domain analysis algorithms at a relatively slower ratecompared to systems that do not include a circuit to extract a powerlevel of a particular frequency band of a sensed bioelectrical brainsignal prior to digitization of the signal. In some examples, sensingmodule 46 may include more than one channel to monitor simultaneousactivity in different frequency bands, i.e., to extract the power levelof more than one frequency band of a sensed bioelectrical brain signal.These frequency bands may include a beta frequency band, e.g.,approximately 10 Hz to approximately 30 Hz, such as about 20 Hz, orother frequency bands.

In some examples, sensing module 46 of IMD 16 may include anarchitecture that merges chopper-stabilization with heterodyne signalprocessing to support a low-noise amplifier. In some examples, sensingmodule 46 may include a frequency selective signal monitor that includesa chopper-stabilized superheterodyne instrumentation amplifier and asignal analysis unit. Example amplifiers that may be included in thefrequency selective signal monitor are described in further detail incommonly-assigned U.S. Patent Application Publication No. 2009/0082691by Denison et al., entitled, “FREQUENCY SELECTIVE MONITORING OFPHYSIOLOGICAL SIGNALS” which was filed on Sep. 25, 2008 and published onMar. 26, 2009. U.S. Patent Application Publication No. 2009/0082691 byDenison et al. is incorporated herein by reference in its entirety.

As described in U.S. Patent Application Publication No. 2009/0082691 byDenison et al., frequency selective signal monitor may utilize aheterodyning, chopper-stabilized amplifier architecture to convert aselected frequency band of a physiological signal to a baseband foranalysis. The physiological signal may include a bioelectrical brainsignal, which may be analyzed in one or more selected frequency bands toselect a stimulation electrode combination in accordance with thetechniques described herein. The frequency selective signal monitor mayprovide a physiological signal monitoring device comprising aphysiological sensing element that receives a physiological signal, aninstrumentation amplifier comprising a modulator that modulates thesignal at a first frequency, an amplifier that amplifies the modulatedsignal, and a demodulator that demodulates the amplified signal at asecond frequency different from the first frequency. A signal analysisunit may analyze a characteristic of the signal in the selectedfrequency band. The second frequency may be selected such that thedemodulator substantially centers a selected frequency band of thesignal at a baseband.

Different movement disorder symptoms may be detected in differentfrequency bands of a bioelectrical brain signal. An example of frequencybands is shown in Table 1 below:

TABLE 1 Frequency (f) Band Hertz (Hz) Frequency Information f < 5 Hz δ(delta frequency band) 5 Hz ≦ f ≦ 10 Hz α (alpha frequency band) 10 Hz ≦f ≦ 30 Hz β (beta frequency band) 50 Hz ≦ f ≦ 100 Hz γ (gamma frequencyband) 100 Hz ≦ f ≦ 200 Hz high γ (high gamma frequency band)

Processor 40 may select the frequency band to monitor based on thepatient's symptoms. As previously indicated, activity of the sensedbioelectrical brain signal within a beta band may be associated withbradykinesia of patient 12. Other symptoms of the patient's movementdisorder may be associated with the energy of a bioelectrical brainsignal within other frequency bands, such as the alpha or high gammabands.

A relative beta band power may include a ratio of a power level in thebeta frequency band of a sensed bioelectrical brain signal to theoverall power of the sensed bioelectrical brain signal. The power levelin the beta band may be determined using any suitable technique. In someexamples, processor 40 may average the power level of the beta band of asensed bioelectrical brain signal over a predetermined time period, suchas about ten seconds to about two minutes, although other time rangesare also contemplated. In other examples, the beta band power level maybe a median power level over a predetermined range of time, such asabout ten seconds to about two minutes. The activity within the betaband of a bioelectrical brain signal, as well as other frequency bandsof interest, may fluctuate over time. Thus, the power level in theselected frequency band at one instant in time may not provide anaccurate and precise indication of the energy of the bioelectrical brainsignal in the selected frequency band. Averaging or otherwise monitoringthe power level in the selected frequency band over time may helpcapture a range of power levels, and, therefore, a better indication ofthe patient's pathological state in the particular brain region sensedby the selected sense electrode combination.

The overall power of the sensed bioelectrical brain signal may bedetermined using any suitable technique. In one example, processor 40may determine an overall power level of a sensed bioelectrical brainsignal based on the total power level of a swept spectrum of thebioelectrical brain signal. To generate the swept spectrum, processor 40may control sensing module 46 to tune to consecutive frequency bandsover time, and processor 40 may assemble a pseudo-spectrogram of thesensed bioelectrical brain signal based on the power level in each ofthe extracted frequency bands. The pseudo-spectrogram may be indicativeof the energy of the frequency content of the bioelectrical brain signalwithin a particular window of time.

In one accordance with example technique, processor 40 may determine anoverall power level of a sensed bioelectrical brain signal based on timedomain data. For example, processor 40 may determine the relative betaband power by determining a ratio of the beta band power to a voltageamplitude of the signal. The voltage amplitude may be a mean or medianvoltage amplitude of the signal over a predetermined range of time, suchas about ten seconds to about two minutes, although other time rangesare also contemplated. The voltage amplitudes of the bioelectrical brainsignals may be calibration coefficients that help minimize variabilitybetween the power levels of the bioelectrical brain signals in aparticular frequency band that is attributable to differences in theoverall signal power level.

Processor 40 may compare the relative beta band power levels of thesensed bioelectrical brain signals (74). Comparing the relative betaband power levels of the bioelectrical brain signals may be moremeaningful than comparing the absolute beta band power levels becausethe signal strength may change depending on the electrodes used to sensethe bioelectrical brain signal. A sensed bioelectrical brain signalhaving a higher overall signal strength may appear to have a higher betaband power level than a second sensed bioelectrical brain signal havinga lower overall signal strength, even though the second sensedbioelectrical signal may have a higher relative beta power.

For example, if a first sense electrode combination includes electrodes24A, 24D and a second sense electrode combination includes electrodes24A, 24B, a first bioelectrical brain signal sensed via the first senseelectrode combination may have a greater overall signal strength, and,therefore, a greater beta band power level than a second bioelectricalbrain signal sensed via the second sense electrode combination due todistance between the electrodes of the first and second sense electrodecombinations. Comparing the relative beta band power levels may reducethe variability in the measured beta band power levels of the sensedbioelectrical signals attributable to variability in the overall signalstrength.

After comparing the relative beta band powers of the sensedbioelectrical brain signals (74), processor 40 may select the senseelectrode combination that is associated with the highest relative betaband power (76). Processor 40 may select a stimulation electrodecombination based on the selected sense electrode combination (78). Aspreviously indicated, memory 42 of IMD 16 may store informationassociating sense and stimulation electrode combinations 56 (FIG. 3). Insome examples, the sense electrode combination and stimulation electrodecombination may comprise the same subset of electrodes 24, 26, while inother examples, the sense and stimulation electrode combinations maycomprise different subsets of electrodes 24, 26.

FIGS. 6A-6D are example power spectral density (PSD) plots ofbioelectrical brain signals sensed via different sense electrodecombinations. The average PSD is shown in microvolts squared per Hertz(μv²/Hz). FIG. 6A illustrates a PSD plot of a first bioelectrical brainsignal 80 sensed via a first sense electrode combination includingelectrodes 24D, 24C of lead 20A (FIG. 3). As shown in FIG. 6A, agreatest power level of the first bioelectrical signal 80 in a beta band(approximately 10 Hz to about 20 Hz) is approximately 58 μv²/Hz. FIG. 6Billustrates a PSD plot of a second bioelectrical brain signal 82 sensedvia a second sense electrode combination including electrodes 24C, 24Bof lead 20A (FIG. 3). As shown in FIG. 6B, a greatest power level of thesecond bioelectrical signal 82 in a beta band is approximately 12μv²/Hz.

FIG. 6C illustrates a PSD plot of a third bioelectrical brain signal 84sensed via a third sense electrode combination including electrodes 24B,24A of lead 20A (FIG. 3). As shown in FIG. 6C, a greatest power level ofthe third bioelectrical signal 84 in a beta band is approximately 11μv²/Hz. FIG. 6D illustrates a PSD plot of a fourth bioelectrical brainsignal 86 sensed via a fourth sense electrode combination includingelectrodes 24B, 24A of lead 20A (FIG. 3). As shown in FIG. 6D, agreatest power level of the fourth bioelectrical signal 86 in a betaband is approximately 30 μv²/Hz.

If the sensed bioelectrical brain signals 80, 82, 84, 86 shown in FIGS.6A-6D, respectively, have substantially similar overall power levels,processor 40 may determine that first bioelectrical brain signal 80 hasthe highest relative beta band power. Accordingly, processor 40 mayselect a stimulation electrode combination based on the first senseelectrode combination by reference memory 42 of IMD 16. As previouslyindicated, memory 42 may store information associating sense electrodecombinations with stimulation electrode combinations.

In some examples, processor 40 may identify an efficacious stimulationelectrode combination for therapy delivery to patient 12 based on afrequency band of a bioelectrical brain signal other than a beta band.FIG. 7 is a flow diagram of an example technique that processor 40 ofIMD 16, processor 60 of programmer 14, or another computing device mayimplement to identify a frequency band of interest. Processor 40 isreferred to throughout the description of FIG. 7. In other examples,processor 60 of programmer 14 or another computing device may implementthe technique shown in FIG. 7 to identify a frequency band of interest.

Processor 40 may generate a spectrogram (e.g., as shown in FIG. 2) of abioelectrical brain signal of patient 12 during a first time period inwhich patient 12 is in a pathological state, e.g., is not receiving anytherapy to manage the movement disorder or other patient condition (90).Processor 40 may generate a spectrogram during a second time period inwhich patient 12 is receiving therapy to manage the movement disorder orother patient condition (92). Processor 40 may determine a frequencyband of interest that indicates a biomarker for the patient's conditionbased on the spectrograms (94). In some examples, processor 40 maydetermine which frequency bands exhibited a relatively large and/ordiscernable change between the first and second time periods. Forexample, in the spectrogram shown in FIG. 2, the beta band activitydecreased after the human subject began receiving a pharmaceutical agentto manage a movement disorder, as indicated by time period 38.

Processor 40 may utilize the frequency band of interest in order toidentify a stimulation electrode combination in accordance with thetechniques described herein. In some examples, processor 40 may sensebioelectrical brain signals within brain 28 of patient 12 with eachsense electrode combination of a plurality of stored sense electrodecombinations. Processor 40 may select a stimulation electrodecombination based on the sense electrode combination associated with asensed bioelectrical brain signal having a greatest relative power levelin the frequency band of interest. In other examples, processor 40 mayselect a stimulation electrode combination based on the sense electrodecombination associated with a sensed bioelectrical brain signal having alowest relative power level in the frequency band of interest.

In some examples, the different sense electrode combinations andassociated beta band power levels may be presented to a user, such as aclinician, via a display of a device, such as programmer 14. FIG. 8 is aflow diagram of an example technique that processor 60 of programmer 14may implement in order to determine the beta band power levels ofbioelectrical brain signals sensed via a respective one of a pluralityof sense electrode combinations. In other examples, processor 40 of IMD16 or another device may perform any part of the technique shown in FIG.8.

Processor 60 may select a sense electrode combination from memory 62(FIG. 4) of programmer 14 (100). Memory 62 may store any number of senseelectrode combinations, which may include, for example, every possiblecombination of electrodes 24, 26 implanted within patient 12 that may beused to sense electrical activity within brain 28. Processor 60 maycontrol IMD 16 to sense a bioelectrical brain signal with the selectedsense electrode combination (102). For example, via the respectivetelemetry modules 64, 50, processor 60 may provide a signal to processor40 of IMD 16 that indicates that processor 40 should controls sensingmodule 46 (FIG. 3) to initiate the measurement of a local fieldpotential within brain 28 via the electrodes of the selected senseelectrode combination. Processor 60 may also transmit the senseelectrode combination to processor 40, such as providing a signalindicating the subset of electrodes 24, 26 in the sense electrodecombination or by providing a signal indicating an identifier associatedwith the selected sense electrode combination. IMD 16 may store senseelectrode combinations within memory 42 and associate each senseelectrode combination with an identifier, such as an alphanumericidentifier.

Processor 60 may receive the sensed bioelectrical brain signal fromprocessor 40 of IMD 16 via the respective telemetry modules 64, 50(FIGS. 3 and 4), and record the bioelectrical brain signal in memory 62of programmer 14 (104). In some examples, instead of or in addition tothe bioelectrical brain signal, processor 60 may record the relativebeta band power of the sensed bioelectrical brain signal in memory 62.After sensing and recording the bioelectrical brain signal with a firstsense electrode combination, processor 60 may determine whether thereare further electrode combinations to test (106). For example, ifprogrammer 14 stores a plurality of sense electrode combinations,processor 60 may record the bioelectrical brain signal sensed via eachof the stored sense electrode combinations.

If there are additional sense electrode combinations with which to sensebioelectrical brain signals (106), processor 60 may determine thebioelectrical brain signal associated with each of the additional senseelectrode combinations (100, 102, 104). If there are no additional senseelectrode combinations available (106), processor 60 may map the senseelectrode combinations to stimulation electrode combinations (108). Thatis, processor 60 may determine the stimulation electrode combinationsthat are associated with the sense electrode combinations. For example,processor 60 may reference a data structure that associates senseelectrode combinations with stimulation electrode combinations in orderto map the sense electrode combinations to stimulation electrodecombinations. In other examples, processor 60 may initialize analgorithm to determine the stimulation electrode combinations that areassociated with the sense electrode combinations if, for example, thesense electrode combinations are not pre-associated with stimulationelectrode combinations.

Processor 60 may present the results to a user (109). As previouslydiscussed, user interface 66 (FIG. 3) of programmer 14 may include adisplay, such as an LCD or LED display. Processor 60 may present theresults of the sensing of bioelectrical brain signals via the differentsense electrode combinations in any suitable manner. In some examples,processor 60 may display a time domain plot of the bioelectrical brainsignal. In other examples, processor 60 may display a table thatprovides the relative beta band (or other frequency band of interest)power level associated with each sense electrode combination.

As previously described, in other examples, processor 40 of IMD 16 oranother device may perform any part of the technique shown in FIG. 8.For example, processor 40 of IMD 16 may select a sense electrodecombination from memory 42 (FIG. 3) of IMD 16 (100) and control sensingmodule 46 to sense a bioelectrical brain signal with the selected senseelectrode combination (102). Processor 40 of IMD 16 may record thebioelectrical brain signal in memory 42, or transmit the signal toprogrammer 24 for recording in memory 62 (104). If there are additionalsense electrode combinations with which to sense bioelectrical brainsignals (106), processor 40 may determine the bioelectrical brain signalassociated with each of the additional sense electrode combinations(100, 102, 104).

Processor 40 may uplink the results to programmer 24. The results mayinclude, for example, the sense electrode combinations tested and theassociated bioelectrical brain signals or specific signalcharacteristics (e.g., beta band power). Programmer 24 may then map thesense electrode combinations to stimulation electrode combinations (108)and present the results to a user (109). In other examples, processor 40of IMD 16 may map the sense electrode combinations to stimulationelectrode combinations (108).

Clinician interaction may be minimized if the technique shown in FIG. 8for sensing bioelectrical brain signals with different sense electrodecombinations is performed by processor 40 of IMD 16. This may help, forexample, reduce the burden on the clinician during the stimulationelectrode combination selection processor. While in some cases, theclinician may initialize the process, processor 40 of IMD 16 may controlthe selection of sense electrode combinations and recording ofbioelectrical brain signals or other signal characteristics.

FIG. 9 is an example table that processor 60 may present to a user via adisplay of programmer 14 (108). A first column of the table shown inFIG. 9 indicates sense electrode combinations. While FIG. 9 indicatesthe sense electrode combinations via alphanumeric indicators (e.g.,“Combination 1”), in other examples, processor 60 may present the senseelectrode combinations to a user using other formats. In some examples,processor 60 may present a graphical display of leads 20 and indicatethe subset of electrodes 24, 26 (FIG. 3) that are selected as part ofeach of the sense electrode combinations.

In some examples, the table shown in FIG. 9 may have selectablesections, such that a user may select one of the sections of the tablein order to retrieve a subset of information associated with theselected section. For example, a user may select the box labeled,“COMBINATION 1” to receive more information about the first senseelectrode combination in the table. The information may include, forexample, the graphical display of the leads 20 and electrodes 24, 26with an indication of the subset of electrodes 24, 26 that are includedin the sense electrode combination associated with the indicator,“COMBINATION 1.” In addition, programmer 14 may present information suchas the stimulation electrode combination associated with the senseelectrode combination, and, in some cases, other stimulation parametervalues that map to or are otherwise related to the sense parameters.

The table shown in FIG. 9 also provides, for each of the sense electrodecombinations, absolute beta band powers of the bioelectrical brainsignal sensed via the respective sense electrode combination. Thesevalues are shown in the column with the headings “β POWER 1” and “βPOWER 2.” The beta band power levels of the bioelectrical brain signalsmay be calculating using different techniques. In some examples, the “βPOWER 1” and “β POWER 2” columns shown in FIG. 9 may provide beta bandpower levels calculated using different techniques. For example, “βPOWER 1” may indicate the average power in the beta band of thebioelectrical signal over a first time period, and “β POWER 2” columnmay indicate the average power in the beta band of the bioelectricalsignal over a second time period that has a different duration than thefirst time period. As an example, the first time period may be about tenseconds and the second time period may be about one minute. Other timeperiod durations are contemplated. The time periods may overlap or maynot overlap.

In other examples, the “β POWER 1” and “β POWER 2” columns shown in FIG.9 may provide beta band power levels calculated in different sub-bandsof the beta band. For example, “β POWER 1” may indicate the averagepower in the 12 Hz sub-band of the beta band of the bioelectricalsignal, and “β POWER 2” may indicate the average power in the 20 Hzsub-band of the beta band of the bioelectrical signal. The power levelsin the different sub-bands of the beta band may be measured at the sameor different times.

For each of the sense electrode combinations, the table shown in FIG. 9may provide the relative beta band power level of the bioelectricalbrain signal sensed via a respective one of the sense electrodecombination. This is shown in the column with the heading “RELATIVEPOWER.” As previously indicated, the relative power may help reduce thevariability in the different beta band power levels (shown in FIG. 9under the heading “β Power 1”) due to the differences in the overallpower level of the sensed bioelectrical brain signals.

In some examples, processor 60 of programmer 14 may also label eachsense electrode combination with a value or other indicator thatindicates the possibility that a stimulation electrode combinationassociated with the sense electrode combination may provide efficacioustherapy to patient 12. This label associated with each sense electrodecombination may help a user compare the different sense electrodecombinations relatively quickly and without undue effort. In the exampleshown in FIG. 9, indicators that processor 60 may present to a user toindicate the possibility that a stimulation electrode combinationassociated with the sense electrode combination may provide efficacioustherapy to patient 12 includes an overall score and a confidence scorefor each sense electrode combination.

The overall score may include, for example, a weighted average of thebeta band power levels in the “β POWER 1” and “β POWER 2” columns of thetable shown in FIG. 9. Different weighting coefficients may be appliedto the power levels in the “β POWER 1” and “β POWER 2” columns in orderto calculate the overall score. The weighting coefficients may indicate,for example, the impact the power level in the “β POWER 1” or “β POWER2” column has on the evaluation of a sense electrode combination. Forexample, if the value in the “β POWER 1” column indicates the averagepower in the 12 Hz sub-band of the beta band of the bioelectricalsignal, and the value in the “β POWER 2” indicates the average power inthe 20 Hz sub-band of the beta band of the bioelectrical signal,processor 60 of programmer 14 may determine that the 20 Hz sub-band ofthe beta band is more revealing of the patient's pathological brainstate. Thus, processor 60 may apply a weighting coefficient to the valuein the “β POWER 2” column to indicate that more weight should be appliedto the “β POWER 2” value when calculating the average of the “β POWER 1”and “β POWER 2” values.

The confidence score may indicate, for example, how well the senseelectrode combinations map to a stimulation electrode combination thatprovides efficacious stimulation therapy to patient 12. For example,processor 60 may store information in memory 62 (FIG. 4) that indicatesthat, based on previous patients or previous trials on patient 12,stimulation delivered with the electrodes of a particular stimulationelectrode combination may not provide efficacious therapy to patient 12,even if the stimulation electrode combination is associated with a senseelectrode combination that sensed a relatively high beta band power.

Processor 60 may also determine the confidence scores based on otherinformation. In some examples, processor 60 may store information inmemory 62 that indicates that for sense electrode combinations thatsensed a bioelectrical brain signal comprising a relative beta bandpower levels at or above a particular threshold value, there is arelatively high probability that stimulation delivery via thestimulation electrode combination associated with the sense electrodecombination may provide efficacious therapy to patient 12. A clinician,manually or with the aid of processor 60, may assign probabilities ofefficacious stimulation to the different relative beta band power levelsbased on past experience with other patients. For example, based onobservations for one or more patients, the clinician may record efficacyscores for each of a plurality of stimulation electrode combinations.The efficacy scores may be associated with different relative beta bandpower levels, which may be the relative beta band power level of abioelectrical brain signal sensed with a sense electrode combinationthat is associated with the respective stimulation electrodecombination.

An efficacy score may indicate the extent to which the patient'ssymptoms were mitigated and, in some cases, a rating of the severity ofside effects from stimulation delivered via a particular stimulationelectrode combination. The efficacy score may be based on subjectiveinformation, e.g., input from the patient, and/or may be based onphysiological parameter measurements. A higher efficacy score may beassociated with a higher probability that stimulation delivery via thestimulation electrode combination associated with the sense electrodecombination may provide efficacious therapy to patient 12.

As an example of how the confidence score may be determined, ifprocessor 60 determines that sense electrode “Combination 1” resulted ina relative beta band power level of 54, and a relative beta band powerlevel at or above 50 is associated with an efficacy rating of 87% inmemory 62, processor 60 determine that stimulation delivery via thestimulation electrode combination associated with sense electrode“Combination 1” may provide efficacious therapy to patient 12 at aconfidence level of about 87%.

In other examples, processor 60 may present a power drain metric (notshown in FIG. 9) for each of the sense electrode combinations. The powerdrain metric may indicate the relative amount of power required toprovide efficacious stimulation to patient 12 if stimulation isdelivered to patient 12 via the stimulation electrode combinationassociated with the sense electrode combination. Some stimulationelectrode combinations may include one electrode, defining a unipolarstimulation configuration, while other stimulation electrodecombinations may include two or more electrodes, defining a bipolarstimulation configuration. The stimulation electrode combinationsincluding fewer active electrodes may draw less current from stimulationgenerator 44 (FIG. 3), resulting in less power drain from power source52 (FIG. 3) of IMD 16. The power drain metric may provide a numeric orother indication of the relative power drain based on factors such asthe number of active electrodes in a stimulation electrode combination.

In some examples, the user may interact with programmer 14 to organizethe sense electrode combinations by any one of the column headings. Forexample, the user may select “β POWER 1” column to organize the senseelectrode combinations in ascending or descending order based on theabsolute beta band powers. As another example, the user may determinethe sense electrode combination that is associated with the highestoverall score by selecting the “OVERALL SCORE” column. In examples inwhich user interface 66 (FIG. 4) of programmer 14 includes a touchscreen display, the user may select a column of the table shown in FIG.9 by selecting the box presented on the display. In other examples, theuser may provide input using other input mechanisms, such as a keypad.

In some examples, a user may select a sense electrode combination fromthe list of combinations shown in FIG. 9 in order to further test thesense electrode combination and/or a stimulation electrode combinationassociated with the sense electrode combination. For example, the usermay select a sense electrode combination by selecting the row of thetable shown in FIG. 9 associated with the sense electrode combination orby manually inputting the sense electrode combination indicator via akeypad of programmer 14. Processor 60 of programmer 14 may receive theuser input selecting the sense electrode combination and present asecond display to the user that allows the user to input values forother stimulation parameters, such as stimulation amplitude, frequency,and pulse rate. Processor 60 may, for example, present a user interfaceincluding text boxes for receiving the values for the other stimulationparameters, pull-down menus that present preset values for the otherstimulation parameter values, and the like.

Processor 60 may also provide a user interface that allows the user toindicate whether the stimulation electrode combination and otherstimulation parameter values should be tested on patient 12. Uponreceiving input from the user indicating a desire to test thestimulation electrode combination and other stimulation parametervalues, processor 60 may provide a signal to processor 40 of IMD 16,which may control stimulation generator 44 (FIG. 3) to generate anddeliver electrical stimulation to patient 12 via the stimulationelectrode combination and the stimulation parameter values provided bythe user.

Although a table is shown in FIG. 9, in other examples, processor 60 maypresent information to a user regarding the sense electrode combinationsand the frequency characteristics of bioelectrical brain signals sensedvia a respective one of the sense electrode combinations in any suitableformat. In addition, processor 60 may present any type of information toa user via a display, such as the table shown in FIG. 9. For example,although not shown in FIG. 9, in some examples, a table presented to auser may include both sense electrode combinations and the associatedstimulation electrode combinations.

In some examples, in addition to a frequency domain characteristic of abioelectrical brain signal sensed via each of a plurality of senseelectrode combinations, a stimulation electrode combination may beselected based on an impedance of an electrical path including theelectrodes of the sense electrode combination that is mapped to thestimulation electrode combination. Thus, in some examples, the tableshown in FIG. 9 may also display a complex impedance value or anelectrical parameter value indicative of the complex impedance value(e.g., a voltage or current amplitude value) for each of the senseelectrode combinations.

A complex impedance of an electrical path between electrodes of thesense electrode combination, and, therefore, through tissue of patient12, may be measured using any suitable technique. In some examples,sensing module 46 (FIG. 3) of IMD 16 may include a chopper-stabilizedsuperheterodyne amplifier shown in FIG. 14 of U.S. Patent ApplicationPublication No. 2009/0082691 by Denison et al. The chopper-stabilizedsuperheterodyne amplifier shown in FIG. 14 of U.S. Patent ApplicationPublication No. 2009/0082691 by Denison et al. includes in-phase andquadrature signal paths with impedance measurement circuitry. Thecomplex impedance may be measured during the same session in which thebioelectrical brain signals of brain 28 are sensed via the plurality ofsense electrode combinations, e.g., a programming session.

The complex impedance measured via each of the sense electrodecombinations may be useful for comparing the sense electrodecombinations. The complex impedance measured via each sense electrodecombination may be revealing of the location of the sense electrodesrelative to the area of the patient's brain affected by the patientcondition. In addition, the impedance measured via each of the senseelectrode combinations may be indicative of the intensity of therapythat may be required to provide efficacious stimulation to patient 12with the associated stimulation electrode combinations. The impedancemay, for example, indicate the coupling efficiency between theelectrodes of the sense electrode combination and the patient's tissue.For example, a relatively high impedance value may indicate that thecoupling efficiency is lower, and, thus, a higher stimulation intensityis required in order to provide efficacious stimulation to patient 12via a stimulation electrode combination associated with the senseelectrode combination. On the other hand, a relatively low impedancevalue may indicate that the stimulation electrode combination associatedwith the sense electrode combination may be useful for providingefficacious therapy to patient 12 at a relatively low intensity, whichmay help conserve the power source 52 (FIG. 3) of IMD 16. Thus, in someexamples, a clinician or a computing device (e.g., programmer 14) maycompare the sense electrode combinations based on the frequency bandcharacteristic and the complex impedance associated with each senseelectrode combination.

After a sense electrode combination is selected, e.g., using thetechnique shown in FIG. 5, processor 40 of IMD 16 may controlstimulation generator 44 (FIG. 3) to generate and deliver electricalstimulation therapy to patient 12 on a chronic basis. Leads 20 may movewithin patient 12 over time, or the patient's disease state may change,such that stimulation delivery via the selected stimulation electrodecombination may no longer provide the most efficacious therapy topatient 12. In some examples, after the selection of a stimulationelectrode combination, processor 40 of IMD 16 may periodically evaluatethe stimulation electrode combination to determine whether anotherstimulation electrode combination may provide more efficacious therapyto patient 12. FIG. 10 is a flow diagram of an example technique thatprocessor 40 may implement in order to evaluate a currently-selectedstimulation electrode combination (referred to as a “first stimulationelectrode combination” in the flow diagram shown in FIG. 10). In otherexamples, processor 60 of programmer 14 or another device may performany part of the technique shown in FIG. 10.

Processor 40 may control switch module 48 (FIG. 3) and stimulationgenerator 44 (FIG. 3) to deliver electrical stimulation to patient 12with a first stimulation electrode combination (110). Processor 40 maycontrol sensing module 46 and switch module 48 to sense a bioelectricalbrain signal with a first sense electrode combination that is associatedwith the first stimulation electrode combination (112). Thisbioelectrical brain signal may include, for example, a local fieldpotential within brain 28. Processor 40 determines a first relative betaband power level of the first bioelectrical brain signal (114), e.g.,using the techniques described above with reference to FIG. 5.

Processor 40 may also evaluate one or more other sense electrodecombinations in order to determine whether stimulation delivery via thefirst stimulation electrode combination is relatively efficacious. Inthe example shown in FIG. 10, processor 40 may select a second senseelectrode combination from memory 42, and sense a second bioelectricalbrain signal via the second sense electrode combination (116). Thesecond sense electrode combination may be associated with a differentstimulation electrode combination than the first sense electrodecombination. Processor 40 determines a second relative beta band powerlevel of the second bioelectrical brain signal (118), e.g., using thetechniques described above with reference to FIG. 5.

In the example shown in FIG. 10, processor 40 compares the first andsecond relative beta band power levels (120). If processor 40 determinesthat the first relative beta band power level is greater than or equalto the second relative beta band power level (120), processor 40 maydetermine that stimulation delivery via the first stimulation electrodecombination is either more efficacious or provides at least the samedegree of efficacy as stimulation delivery via the second stimulationelectrode combination. If the first relative beta band power is greaterthan the second relative beta band power level, processor 40 maydetermine that the first stimulation electrode combination providesstimulation therapy to a more relevant target tissue site within brain28 than the second stimulation electrode combination. Thus, processor 40may continue controlling switch module 48 and stimulation generator 44to deliver electrical stimulation to patient 12 with the firststimulation electrode combination (110).

If processor 40 determines that the first relative beta band power levelis not greater than or equal to the second relative beta band powerlevel (122), processor 40 may determine that the second stimulationelectrode combination provides stimulation therapy to a more relevanttarget tissue site within brain 28 than the first stimulation electrodecombination. Thus, processor 40 may deliver stimulation to brain 28 withthe second stimulation electrode combination associated with the secondsense electrode combination (122). In other examples, processor 40 maysense bioelectrical brain signals with additional sense electrodecombinations in order to determine whether stimulation delivery with thesecond stimulation electrode combination provides relatively efficacioustherapy.

In some examples, processor 40 may also measure the impedance of theelectrical paths through tissue via each of the sense electrodecombinations in order to further evaluate the stimulation electrodecombinations, as described above with respect to FIG. 9. For example,upon determining that the impedance measured via the first senseelectrode combination associated with the first stimulation electrodecombination has increased by a threshold amount, processor 40 may beginevaluating other stored sense electrode combinations to determinewhether another stimulation electrode combination may provide moreefficacious therapy to patient 12, e.g., with lower power consumption.

Various examples of the disclosure have been described. These and otherexamples are within the scope of the following example claims.

What is claimed is:
 1. A method comprising: receiving, by a processor ofa therapy system, a plurality of bioelectrical signals, wherein each ofthe bioelectrical signals is sensed within a patient by a sensing modulewith a respective sense electrode combination of a plurality of senseelectrode combinations, each of the sense electrode combinations beingassociated with a respective one of a plurality of stimulation electrodecombinations; for each of the sense electrode combinations, generating,by the processor, an indicator based on the bioelectrical signal sensedwith the respective sense electrode combination, wherein the indicatorindicates a possibility that electrical stimulation delivered by amedical device with the stimulation electrode combination associatedwith the sense electrode combination will provide efficacious therapy tothe patient, and wherein generating the indicator comprises comparing acharacteristic of the bioelectrical signal sensed with the respectivesense electrode combination with stored information; and presenting, viaa display, indications of the sense electrode combinations and therespective indicators.
 2. The method of claim 1, wherein generating theindicator comprises generating, for each of the sense electrodecombinations, the indicator based on a frequency domain characteristicof the bioelectrical signal sensed with the respective sense electrodecombination.
 3. The method of claim 2, wherein generating the indicatorcomprises generating the indictor based on a weighted average of betaband power levels of the bioelectrical signal sensed with the respectivesense electrode combination.
 4. The method of claim 2, whereingenerating the indicator based on the frequency domain characteristiccomprises: determining the frequency domain characteristic of thebioelectrical signal sensed with the respective sense electrodecombination; and comparing the frequency domain characteristic to storedinformation, wherein the stored information is based on at least one ofbioelectrical signals sensed within other patients or bioelectricalsignals previously sensed within the patient.
 5. The method of claim 1,wherein the stored information indicates, for each stored bioelectricalbrain signal of a plurality of stored bioelectrical brain signals, anoutcome of electrical stimulation therapy delivered via a stimulationelectrode combination associated with the stored bioelectrical brainsignal.
 6. The method of claim 1, wherein generating the indicatorcomprises generating a confidence score that indicates whether thestimulation electrode combination associated with the sense electrodecombination will provide efficacious stimulation therapy to the patient.7. The method of claim 6, wherein generating the confidence scorecomprises comparing the characteristic of the bioelectrical signal withthe stored information, the stored information indicating at least oneof efficacious or inefficacious stimulation electrode combinationsdetermined based on testing of the stimulation electrode combinations ona group of patients.
 8. The method of claim 6, wherein generating theconfidence score comprises comparing the characteristic of thebioelectrical signal with the stored information, the stored informationindicating at least one of efficacious or inefficacious stimulationelectrode combinations for the patient, and the stored information beingbased on previous testing of the stimulation electrode combinations onthe patient.
 9. The method of claim 6, wherein generating the confidencescore comprises comparing the characteristic of the bioelectrical signalwith the stored information, the stored information associating aprobability of efficacious stimulation with the respective senseelectrode combination.
 10. The method of claim 9, wherein theprobability of efficacious stimulation is based on historical data fromone or more other patients.
 11. The method of claim 9, wherein theprobability of efficacious stimulation is based on a frequency domaincharacteristic of the bioelectrical brain signal sensed with therespective sense electrode combination.
 12. The method of claim 9,wherein the stored information associates a relatively high probabilityof efficacious stimulation with the stimulation electrode combinationassociated with a sense electrode combination with which a bioelectricalbrain signal exhibiting a relative beta band power level at or above athreshold value was sensed.
 13. The method of claim 9, furthercomprising generating the probability of efficacious stimulation for asense electrode combination, wherein generating the probability ofefficacious stimulation comprises: determining the frequency domaincharacteristic of a bioelectrical brain signal sensed via the senseelectrode combination; determining an efficacy score associated with thefrequency domain characteristic in a memory; and generating theprobability of efficacious stimulation based on the efficacy score. 14.The method of claim 13, wherein the efficacy score indicates at leastone of an extent to which symptoms are mitigated or a rating of theseverity of side effects from electrical stimulation delivered via thestimulation electrode combination associated with the sense electrodecombination.
 15. The method of claim 1, further comprising selecting, bythe processor, at least one of the stimulation electrode combinationsbased on the generated indicators.
 16. The method of claim 15, furthercomprising controlling the medical device to deliver electricalstimulation to the patient via the at least one of the stimulationelectrode combinations selected based on the generated indicators. 17.The method of claim 1, wherein at least one of the sense electrodecombinations includes at least one of a partial ring electrode or asegmented electrode.
 18. The method of claim 1, wherein at least one ofthe sense electrode combinations includes a ring electrode.
 19. A systemcomprising: a memory; and a processor configured to receive a pluralityof bioelectrical signals, wherein each of the bioelectrical signals issensed within a patient by a sensing module with a respective senseelectrode combination of a plurality of sense electrode combinations,each of the sense electrode combinations being associated with arespective one of a plurality of stimulation electrode combinations,and, for each of the sense electrode combinations, generate an indicatorbased on the bioelectrical signal sensed with the respective senseelectrode combination, wherein the indicator indicates a possibilitythat electrical stimulation delivered by a medical device with thestimulation electrode combination associated with the sense electrodecombination will provide efficacious therapy to the patient, wherein theprocessor is configured to store the indicators in the memory, andwherein the processor is configured to generate the indicator by atleast comparing a characteristic of the bioelectrical signal sensed withthe respective sense electrode combination with information stored bythe memory.
 20. The system of claim 19, further comprising a display,wherein the processor is configured to present, via the display, a listof the sense electrode combinations and the respective indicators. 21.The system of claim 19, wherein the processor is configured to generatethe indicator based on a frequency domain characteristic of thebioelectrical signal sensed with the respective sense electrodecombination.
 22. The system of claim 21, wherein the frequency domaincharacteristic comprises a weighted average of beta band power levels ofthe bioelectrical signal sensed with the respective sense electrodecombination.
 23. The system of claim 21, wherein the processor isconfigured to generate the indicator by at least determining thefrequency domain characteristic of the bioelectrical signal sensed withthe respective sense electrode combination, and comparing the frequencydomain characteristic to the information stored by the memory, whereinthe information is based on at least one of bioelectrical signals sensedwithin other patients or bioelectrical signals previously sensed withinthe patient.
 24. The system of claim 19, wherein the information storedby the memory indicates, for each stored bioelectrical brain signal of aplurality of stored bioelectrical brain signals, an outcome ofelectrical stimulation therapy delivered via a stimulation electrodecombination associated with the stored bioelectrical brain signal. 25.The system of claim 19, wherein the processor is configured to generatethe indicator by at least generating, for each of the sense electrodecombinations, a confidence score that indicates whether the stimulationelectrode combination associated with the respective sense electrodecombination will provide efficacious stimulation therapy to the patient.26. The system of claim 25, wherein the processor is configured togenerate the confidence score by at least comparing the characteristicof the bioelectrical signal sensed with the respective sense electrodecombination with the information stored by the memory, the informationindicating at least one of efficacious or inefficacious stimulationelectrode combinations determined based on testing of the stimulationelectrode combinations on a group of patients.
 27. The system of claim25, wherein the processor is configured to generate the confidence scoreby at least comparing the characteristic of the bioelectrical signalsensed with the respective sense electrode combination with theinformation stored by the memory, the information associating aprobability of efficacious stimulation with the sense electrodecombination.
 28. The system of claim 27, wherein the probability ofefficacious stimulation is based on historical data from one or moreother patients.
 29. The system of claim 27, wherein the probability ofefficacious stimulation is based on a frequency domain characteristic ofthe bioelectrical brain signal sensed with the respective senseelectrode combination.
 30. The system of claim 27, wherein theinformation associates a relatively high probability of efficaciousstimulation with the stimulation electrode combination associated with asense electrode combination with which a bioelectrical brain signalexhibiting a relative beta band power level at or above a thresholdvalue was sensed.
 31. The system of claim 27, wherein the processor isfurther configured to generate the probability of efficaciousstimulation for a sense electrode combination by at least: determiningthe frequency domain characteristic of the bioelectrical brain signalsensed via the sense electrode combination; determining an efficacyscore associated with the frequency domain characteristic in a memory;and generating the probability of efficacious stimulation based on theefficacy score.
 32. The system of claim 31, wherein the efficacy scoreindicates at least one of an extent to which symptoms are mitigated or arating of the severity of side effects from electrical stimulationdelivered via the stimulation electrode combination associated with thesense electrode combination.
 33. The system of claim 25, wherein theprocessor is configured to generate the confidence score by at leastcomparing the characteristic of the bioelectrical signal sensed with therespective sense electrode combination with the information stored bythe memory, the information indicating at least one of efficacious orinefficacious stimulation electrode combinations for the patient, andthe information being based on previous testing of the stimulationelectrode combinations on the patient.
 34. The system of claim 19,wherein the processor is further configured to select at least one ofthe stimulation electrode combinations based on the generatedindicators.
 35. The system of claim 34, further comprising the medicaldevice, wherein the processor is configured to control the medicaldevice to deliver electrical stimulation to the patient via the at leastone of the stimulation electrode combinations selected based on thegenerated indicators.
 36. The system of claim 19, wherein at least oneof the sense electrode combinations includes at least one of a partialring electrode or a segmented electrode.
 37. The system of claim 19,wherein at least one of the sense electrode combinations includes a ringelectrode.
 38. A system comprising: means for receiving a plurality ofbioelectrical signals, wherein each of the bioelectrical signals issensed within a patient by a sensing module with a respective senseelectrode combination of a plurality of sense electrode combinations,each of the sense electrode combinations being associated with arespective one of a plurality of stimulation electrode combinations; andmeans for generating, for each of the sense electrode combinations, anindicator based on the bioelectrical signal sensed with the respectivesense electrode combination by at least comparing a characteristic ofthe bioelectrical signal sensed with the respective sense electrodecombination with stored information, wherein the indicator indicates apossibility that electrical stimulation delivered by a medical devicewith the stimulation electrode combination associated with the senseelectrode combination will provide efficacious therapy to the patient.39. The system of claim 38, wherein the means for generating theindicator generates the indicator by at least determining a frequencydomain characteristic of the bioelectrical signal sensed with therespective sense electrode combination and comparing the frequencydomain characteristic to stored information, wherein the storedinformation is based on at least one of bioelectrical signals sensedwithin other patients or bioelectrical signals previously sensed withinthe patient.
 40. A non-transitory computer-readable medium comprisinginstructions that, when executed by a processor, cause the processor to:receive a plurality of bioelectrical signals, wherein each of thebioelectrical signals is sensed within a patient by a sensing modulewith a respective sense electrode combination of a plurality of senseelectrode combinations, each of the sense electrode combinations beingassociated with a respective one of a plurality of stimulation electrodecombinations; and for each of the sense electrode combinations, generatean indicator based on the bioelectrical signal sensed with therespective sense electrode combination by at least comparing acharacteristic of the bioelectrical signal with stored information,wherein the indicator indicates a possibility that electricalstimulation delivered by a medical device with the stimulation electrodecombination associated with the sense electrode combination will provideefficacious therapy to the patient.
 41. The computer-readable medium ofclaim 40, further comprising instructions that, when executed by theprocessor, cause the processor to generate the indicator by at least:determining a frequency domain characteristic of the bioelectricalsignal sensed with the respective sense electrode combination; andcomparing the frequency domain characteristic to stored information,wherein the stored information is based on at least one of bioelectricalsignals sensed within other patients or bioelectrical signals previouslysensed within the patient.